Learn about Statistics for ML with interactive visualizations and depth.
Course Modules
Descriptive Statistics
Master the foundations of data analysis with interactive visualizations. Learn Central Tendency, Spread, Outliers, and EDA techniques using Python.
Inferential Statistics
Master the art of drawing conclusions from data. Learn the Central Limit Theorem, Hypothesis Testing, and Confidence Intervals with interactive visualizations and Python code.
Estimation Theory
Master the fundamental techniques of statistical estimation. Learn how to infer population parameters from sample data using Maximum Likelihood Estimation (MLE), Bayesian methods (MAP), and the Method of Moments.
Regression Analysis
Master Regression Analysis: From Simple Linear Regression and Gauss-Markov intuition to Residual Analysis and Regularization (Lasso/Ridge) with Go, Java, and Python.
Non-Parametric Methods
Learn about Non-Parametric Methods with interactive visualizations and depth.